Compliance Templates

Uncontrolled exfiltration of cardholder data, PHI, or PII creates regulatory exposure, investigation burden, and reputational harm. SafeSquid Text Analyser supports pattern-based detection for PCI, HIPAA, GDPR, and custom data. Use these templates as a starting point for detection and enforcement, not as a substitute for a full compliance program.

Problem: Sensitive data in transit requires detection for compliance

Organizations must detect and control sensitive data in web traffic to meet PCI-DSS, HIPAA, GDPR, and similar requirements. Failure to detect cardholder data, PHI, or PII in transit creates regulatory and legal risk. SafeSquid Text Analyser supports pattern-based detection so administrators can block or log matches and demonstrate control operation to auditors.

Key benefits

Pre-built patterns reduce implementation time for PCI-DSS, HIPAA, GDPR, and similar programs. Organizations can show auditors configured detection rules and logs of matches or blocks. Combine templates with Access Restriction to block, log, or alert on matches after tuning.

Prerequisites

HTTPS inspection enabled so SafeSquid can inspect request/response body content. See Configure HTTPS Inspection.
Access to Configure → Real Time Content Security → Text Analyser in the Configuration Portal.
Decision on which regulations apply and which data types to protect (assess before configuring).

Pre-built patterns for regulatory requirements

SafeSquid’s Text Analyser supports pattern-based detection of sensitive data. Use the sections below as starting points for PCI-DSS, HIPAA, GDPR, and other regulatory requirements. :::note These templates provide detection patterns only. They do not by themselves make an environment compliant. Combine them with Access Restriction, HTTPS inspection, logging, governance, retention, and review processes. :::

PCI-DSS (Payment Card Industry)

Detect credit card numbers, CVV codes, and cardholder data in transit.

Credit Card Number Patterns

Card Type	Pattern (Regex)	Example
Visa	`4[0-9]{12}(?:[0-9]{3})?`	4111111111111111
Mastercard	`5[1-5][0-9]{14}`	5500000000000004
American Express	`3[47][0-9]{13}`	340000000000009
Discover	`6(?:011\|5[0-9]{2})[0-9]{12}`	6011000000000004
All Major Cards	`(?:4[0-9]{12}(?:[0-9]{3})?\|5[1-5][0-9]{14}\|3[47][0-9]{13}\|6(?:011\|5[0-9]{2})[0-9]{12})`	—

Configuration Example

Navigate to Configure → Real Time Content Security → Text Analyser
Add a new policy with:
- Comment: PCI-DSS Credit Card Detection
- Mime type: text/.*|application/json|application/xml
- Keyword(s): (?:4[0-9]{12}(?:[0-9]{3})?|5[1-5][0-9]{14}|3[47][0-9]{13})
- Score: 100
Set Threshold to 100 to block on first match

Additional PCI Patterns

Data Type	Pattern
CVV/CVC	`\b[0-9]{3,4}\b` (use with context)
Expiry Date	`(0[1-9]\|1[0-2])\/([0-9]{2}\|[0-9]{4})`
Track Data	`%B[0-9]{13,19}\^[A-Z\s]{2,26}\^[0-9]{4}`

HIPAA (Healthcare)

Detect Protected Health Information (PHI) including medical record numbers, SSNs, and health-related terms.

Format	Pattern
With dashes	`[0-9]{3}-[0-9]{2}-[0-9]{4}`
Without dashes	`(?<![0-9])[0-9]{9}(?![0-9])`
Both formats	`[0-9]{3}-?[0-9]{2}-?[0-9]{4}`

Medical Record Identifiers

Data Type	Pattern	Notes
MRN (generic)	`MRN[:\s]?[0-9]{6,10}`	Prefix-based
NPI (Provider)	`[0-9]{10}`	National Provider Identifier
DEA Number	`[A-Z]{2}[0-9]{7}`	Drug Enforcement Administration

PHI Keywords (High-Risk Terms)

(diagnosis|prognosis|treatment|prescription|medication|patient|medical.record|health.insurance|HIV|AIDS|cancer|diabetes|mental.health|psychiatric|substance.abuse)

Configuration Example

Create a Text Analyser policy:
- Comment: HIPAA PHI Detection
- Keyword(s): SSN pattern + PHI keywords
- Score: 50 per match
Set Threshold to 100 (blocks when multiple indicators present)

Detect Personally Identifiable Information (PII) for EU data subjects.

EU National ID Patterns

Country	Data Type	Pattern
UK	National Insurance	`[A-Z]{2}[0-9]{6}[A-Z]`
Germany	Personalausweis	`[0-9]{10}`
France	INSEE	`[12][0-9]{2}(0[1-9]\|1[0-2])[0-9]{8}`
Spain	DNI	`[0-9]{8}[A-Z]`
Italy	Codice Fiscale	`[A-Z]{6}[0-9]{2}[A-Z][0-9]{2}[A-Z][0-9]{3}[A-Z]`

IBAN (Bank Account)

[A-Z]{2}[0-9]{2}[A-Z0-9]{4}[0-9]{7}([A-Z0-9]?){0,16}

Email Addresses

[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}

Phone Numbers (International)

\+?[0-9]{1,3}[-.\s]?(\([0-9]{1,4}\)|[0-9]{1,4})[-.\s]?[0-9]{1,4}[-.\s]?[0-9]{1,9}

(personal.data|data.subject|consent|right.to.erasure|data.portability|processing.agreement|controller|processor|DPO|data.protection)

Financial Services

Bank Account Numbers

Type	Pattern
US Routing	`[0-9]{9}`
US Account	`[0-9]{10,12}`
SWIFT/BIC	`[A-Z]{6}[A-Z0-9]{2}([A-Z0-9]{3})?`

Tax Identifiers

Country	Type	Pattern
US	EIN	`[0-9]{2}-[0-9]{7}`
US	ITIN	`9[0-9]{2}-[0-9]{2}-[0-9]{4}`
UK	UTR	`[0-9]{10}`

Intellectual Property

Source Code Detection

Detect code snippets that may indicate IP leakage:

(function\s+[a-zA-Z_]+\s*\(|class\s+[A-Z][a-zA-Z]+|import\s+[a-z]+|#include\s*<|package\s+[a-z]+|def\s+[a-z_]+\s*\()

Confidential Markers

(CONFIDENTIAL|PROPRIETARY|TRADE.SECRET|INTERNAL.ONLY|DO.NOT.DISTRIBUTE|NDA|RESTRICTED)

Implementation Guidelines

Step 1: Assess Requirements

Identify which regulations apply to the organization and which data types require protection.

Step 2: Configure Detection

Add Text Analyser policies using patterns from this document. Start with logging or limited pilot enforcement to assess false positive rates.

Step 3: Tune Thresholds

Adjust scores and thresholds based on observed traffic:

High threshold (200+): Reduces false positives, may miss some violations
Medium threshold (100): Balanced detection
Low threshold (50): Aggressive detection, more false positives

Step 4: Enable Enforcement

After tuning, enable blocking for high-confidence matches. Avoid broad hard enforcement before you have verified false-positive behavior on real traffic.

Step 5: Monitor and Report

Use Reporting Module to track DLP events for compliance audits.

Verification and Evidence

Interface: Configure → Real Time Content Security → Text Analyser shows policies with patterns, scores, and thresholds. Access Restriction policies reference the same profiles for block/log actions.
Logs: Security and access logs record matches and blocked requests when threshold is exceeded. Filter logs by DLP or Text Analyser events.
Audit evidence: Export reports from the Reporting Module for the audit period; show configured patterns and count of matches or blocks to demonstrate control operation.
Governance check: Retain the rationale for each enabled pattern and the tuning record that shows why the threshold is safe enough for production.

Troubleshooting

Issue	Resolution
No matches detected	Confirm HTTPS inspection is enabled; check MIME type and keyword pattern match request/response body. Run in log-only mode first to verify detection.
Too many false positives	Increase score threshold or narrow patterns; use Request Profiles to restrict detection to high-risk channels.
Block not triggering	Ensure Access Restriction policy references the Text Analyser profile and action is Block; check policy order.

Custom Templates

Create organization-specific patterns for:

Employee ID formats
Internal project codes
Customer account numbers
Proprietary terminology

​Compliance Templates

​Problem: Sensitive data in transit requires detection for compliance

​Key benefits

​Prerequisites

​Pre-built patterns for regulatory requirements

​PCI-DSS (Payment Card Industry)

​Credit Card Number Patterns

​Configuration Example

​Additional PCI Patterns

​HIPAA (Healthcare)

​Social Security Number

​Medical Record Identifiers

​PHI Keywords (High-Risk Terms)

​Configuration Example

​GDPR (European Union)

​EU National ID Patterns

​IBAN (Bank Account)

​Email Addresses

​Phone Numbers (International)

​GDPR-Sensitive Keywords

​Financial Services

​Bank Account Numbers

​Tax Identifiers

​Intellectual Property

​Source Code Detection

​Confidential Markers

​Implementation Guidelines

​Step 1: Assess Requirements

​Step 2: Configure Detection

​Step 3: Tune Thresholds

​Step 4: Enable Enforcement

​Step 5: Monitor and Report

​Verification and Evidence

​Troubleshooting

​Custom Templates

Compliance Templates

Problem: Sensitive data in transit requires detection for compliance

Key benefits

Prerequisites

Pre-built patterns for regulatory requirements

PCI-DSS (Payment Card Industry)

Credit Card Number Patterns

Configuration Example

Additional PCI Patterns

HIPAA (Healthcare)

Social Security Number

Medical Record Identifiers

PHI Keywords (High-Risk Terms)

Configuration Example

GDPR (European Union)

EU National ID Patterns

IBAN (Bank Account)

Email Addresses

Phone Numbers (International)

GDPR-Sensitive Keywords

Financial Services

Bank Account Numbers

Tax Identifiers

Intellectual Property

Source Code Detection

Confidential Markers

Implementation Guidelines

Step 1: Assess Requirements

Step 2: Configure Detection

Step 3: Tune Thresholds

Step 4: Enable Enforcement

Step 5: Monitor and Report

Verification and Evidence

Troubleshooting

Custom Templates